chr2.12973_chr2_25781101_25782435_+_1.R 

fitVsDatCorrelation=0.923903225334785
cont.fitVsDatCorrelation=0.271669740233233

fstatistic=8565.23132186393,52,692
cont.fstatistic=1342.69362701771,52,692

residuals=-1.08230689985485,-0.0970986751644987,0.00543048824397899,0.104062726037984,0.843176778003995
cont.residuals=-1.04241259970349,-0.345963338876037,-0.0904543515231467,0.3225167935002,1.27326662234307

predictedValues:
Include	Exclude	Both
chr2.12973_chr2_25781101_25782435_+_1.R.tl.Lung	89.9479400070726	105.718852214485	96.5662400627037
chr2.12973_chr2_25781101_25782435_+_1.R.tl.cerebhem	79.7839254294749	101.136329523495	101.176611609471
chr2.12973_chr2_25781101_25782435_+_1.R.tl.cortex	94.9326416216277	79.5947167576979	103.316116152498
chr2.12973_chr2_25781101_25782435_+_1.R.tl.heart	98.5817174878152	84.229070969443	109.641529395409
chr2.12973_chr2_25781101_25782435_+_1.R.tl.kidney	92.598035677014	100.990075598997	96.7815003491638
chr2.12973_chr2_25781101_25782435_+_1.R.tl.liver	91.0750799067447	108.842934205798	92.8192743861583
chr2.12973_chr2_25781101_25782435_+_1.R.tl.stomach	89.5923342959828	108.316630461358	101.195354882101
chr2.12973_chr2_25781101_25782435_+_1.R.tl.testicle	92.6457220715804	102.190844390304	94.1977235635066


diffExp=-15.7709122074123,-21.3524040940198,15.3379248639299,14.3526465183722,-8.39203992198259,-17.7678542990529,-18.7242961653752,-9.54512231872413
diffExpScore=1.92871829162126
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,-1,0,0,0,0,-1,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	96.5845336221698	94.7856382174173	97.5655721880456
cerebhem	97.4201971271716	112.286358088877	105.742789297843
cortex	111.159188601907	94.7117391164788	110.41882256719
heart	113.936359326730	97.8577012812647	108.832732752786
kidney	115.705033402172	94.3103629081313	98.8018143906803
liver	102.638485271268	106.795374142497	100.016303095396
stomach	98.617812796658	111.146469638368	105.830782010079
testicle	111.08873136098	115.282826585677	100.574291826789
cont.diffExp=1.79889540475251,-14.8661609617057,16.4474494854278,16.0786580454655,21.3946704940410,-4.15688887122958,-12.5286568417101,-4.19409522469680
cont.diffExpScore=4.36092474375552

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,0,0,0
cont.diffExp1.4Score=0
cont.diffExp1.3=0,0,0,0,0,0,0,0
cont.diffExp1.3Score=0
cont.diffExp1.2=0,0,0,0,1,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.534505967289005
cont.tran.correlation=-0.365906876749584

tran.covariance=-0.00373481301353974
cont.tran.covariance=-0.00233177301548284

tran.mean=95.0110531636806
cont.tran.mean=104.645425717986

weightedLogRatios:
wLogRatio
Lung	-0.739910112391185
cerebhem	-1.06666407679176
cortex	0.78683195340363
heart	0.709977312487381
kidney	-0.396609970995315
liver	-0.819961294486281
stomach	-0.871162403139757
testicle	-0.448897127947859

cont.weightedLogRatios:
wLogRatio
Lung	0.085750421693035
cerebhem	-0.660393638561815
cortex	0.741524592752102
heart	0.708841191072681
kidney	0.950464987796903
liver	-0.184654905692466
stomach	-0.556251558666722
testicle	-0.1752477600568

varWeightedLogRatios=0.512247716813949
cont.varWeightedLogRatios=0.381410866692655

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.47046867845506	0.089601204788815	49.8929527676743	2.04178495173976e-231	***
df.mm.trans1	-0.212415742950355	0.0758781419834536	-2.79943258226692	0.0052618956209094	** 
df.mm.trans2	0.167824324426661	0.0689072629640464	2.43550994782983	0.0151222667298734	*  
df.mm.exp2	-0.210861260226103	0.0892714507186143	-2.36202345238841	0.0184514274631279	*  
df.mm.exp3	-0.297463147290174	0.0892714507186143	-3.33211956225272	0.000907711850611158	***
df.mm.exp4	-0.262575367656330	0.0892714507186143	-2.94131399840218	0.00337737189814835	** 
df.mm.exp5	-0.0189507779211643	0.0892714507186143	-0.212282625280703	0.831949061727385	   
df.mm.exp6	0.0811506833067918	0.0892714507186143	0.909032872811495	0.363649257674502	   
df.mm.exp7	-0.0265094854703943	0.0892714507186143	-0.296953676197700	0.766590986753492	   
df.mm.exp8	0.0204437588509762	0.0892714507186143	0.229006683395517	0.818931384581248	   
df.mm.trans1:exp2	0.0909522500691813	0.0789885750272631	1.15146082883238	0.249940379495332	   
df.mm.trans2:exp2	0.166547431338828	0.0627077805917765	2.65592929245959	0.00809115937524285	** 
df.mm.trans1:exp3	0.351399693243387	0.0789885750272631	4.44874075930728	1.00626051540965e-05	***
df.mm.trans2:exp3	0.0136276327135765	0.0627077805917764	0.217319646541017	0.828023305813642	   
df.mm.trans1:exp4	0.354230132455325	0.0789885750272631	4.48457428600354	8.5515342955052e-06	***
df.mm.trans2:exp4	0.0353322574020658	0.0627077805917764	0.563442958252286	0.573315817440737	   
df.mm.trans1:exp5	0.0479876477561704	0.0789885750272631	0.607526439609872	0.543700905779695	   
df.mm.trans2:exp5	-0.026810204295077	0.0627077805917764	-0.42754191014365	0.669117673848304	   
df.mm.trans1:exp6	-0.0686975216404822	0.0789885750272631	-0.869714659579199	0.384757925202365	   
df.mm.trans2:exp6	-0.0520280436966614	0.0627077805917765	-0.829690402142607	0.406999966968585	   
df.mm.trans1:exp7	0.0225481884580098	0.0789885750272631	0.285461390463459	0.775376101245058	   
df.mm.trans2:exp7	0.0507849540548528	0.0627077805917764	0.8098668709942	0.418295088665555	   
df.mm.trans1:exp8	0.0091079612137951	0.0789885750272631	0.115307324010485	0.908234983713953	   
df.mm.trans2:exp8	-0.0543849031498977	0.0627077805917764	-0.867275203119368	0.386091871290457	   
df.mm.trans1:probe2	-0.0372651538143809	0.0550258541505237	-0.677229902010093	0.49848643232664	   
df.mm.trans1:probe3	0.262804434112832	0.0550258541505237	4.77601734984301	2.18364408037091e-06	***
df.mm.trans1:probe4	-0.00284093987448352	0.0550258541505237	-0.0516291826513424	0.958839065314934	   
df.mm.trans1:probe5	-0.00368968826884686	0.0550258541505237	-0.0670537209427715	0.94655830449865	   
df.mm.trans1:probe6	-0.0371342695889934	0.0550258541505237	-0.674851306940412	0.49999564350782	   
df.mm.trans1:probe7	0.184457964972622	0.0550258541505237	3.3522053918152	0.000845325360687706	***
df.mm.trans1:probe8	-0.297830068061487	0.0550258541505237	-5.41254784063452	8.57400685581805e-08	***
df.mm.trans1:probe9	1.09868984035861	0.0550258541505237	19.9667930161180	2.15577800428305e-70	***
df.mm.trans1:probe10	0.947584078620863	0.0550258541505237	17.2207063979187	1.40765147790492e-55	***
df.mm.trans1:probe11	0.844288176024321	0.0550258541505237	15.3434815153394	5.97428761314403e-46	***
df.mm.trans1:probe12	0.836223461161129	0.0550258541505237	15.1969192313423	3.20893914601007e-45	***
df.mm.trans1:probe13	0.900931675011311	0.0550258541505237	16.3728794204049	3.60476421731098e-51	***
df.mm.trans1:probe14	1.0920554436557	0.0550258541505237	19.8462242979159	9.9555327412526e-70	***
df.mm.trans2:probe2	0.213064176134712	0.0550258541505237	3.87207394458382	0.000118139672925188	***
df.mm.trans2:probe3	0.194095353832159	0.0550258541505237	3.52734831341663	0.000447468609244615	***
df.mm.trans2:probe4	0.263290819524160	0.0550258541505237	4.78485656585948	2.09265802704836e-06	***
df.mm.trans2:probe5	-0.262006600192071	0.0550258541505237	-4.76151809430072	2.34119278847972e-06	***
df.mm.trans2:probe6	-0.0261098401193787	0.0550258541505237	-0.474501314381327	0.63529215860284	   
df.mm.trans3:probe2	-0.195765129253430	0.0550258541505237	-3.55769360195505	0.000399661361553393	***
df.mm.trans3:probe3	0.83323196174293	0.0550258541505237	15.1425538886433	5.97447442201692e-45	***
df.mm.trans3:probe4	0.370435154424578	0.0550258541505237	6.73202006844363	3.51593380774541e-11	***
df.mm.trans3:probe5	-0.313065858864687	0.0550258541505237	-5.68943206239549	1.88203595689330e-08	***
df.mm.trans3:probe6	-0.264347622841844	0.0550258541505237	-4.80406214356472	1.90737462940327e-06	***
df.mm.trans3:probe7	-0.0718549963587153	0.0550258541505237	-1.30584063560659	0.192040686771294	   
df.mm.trans3:probe8	-0.175367961932165	0.0550258541505237	-3.18701026343805	0.00150217936621923	** 
df.mm.trans3:probe9	1.23867793134699	0.0550258541505237	22.5108351423055	1.27643369248481e-84	***
df.mm.trans3:probe10	0.0470836449307778	0.0550258541505237	0.855664044795745	0.392479802368236	   
df.mm.trans3:probe11	0.118844199772926	0.0550258541505237	2.15978836871531	0.0311318365134025	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.53549155223406	0.225367070072479	20.1249080035314	2.88816248558425e-71	***
df.mm.trans1	0.0246766143093932	0.190850497843855	0.129298139581394	0.897159314843821	   
df.mm.trans2	0.0392220024560935	0.173317178017003	0.226301875583537	0.821033466485177	   
df.mm.exp2	0.0975644635932798	0.22453766483378	0.434512684833988	0.664051640804063	   
df.mm.exp3	0.0160088095696374	0.22453766483378	0.0712967669877942	0.943182168060958	   
df.mm.exp4	0.0878304590855274	0.22453766483378	0.391161363286406	0.69579837118403	   
df.mm.exp5	0.163007408939896	0.22453766483378	0.725969111064582	0.46810316319095	   
df.mm.exp6	0.155282535234503	0.22453766483378	0.69156564601068	0.48944208842488	   
df.mm.exp7	0.098747521902987	0.22453766483378	0.439781548347746	0.660232645189992	   
df.mm.exp8	0.30530922179759	0.22453766483378	1.35972386647738	0.174360179711758	   
df.mm.trans1:exp2	-0.0889495327084511	0.198673932622351	-0.447716172596889	0.654498168545503	   
df.mm.trans2:exp2	0.0718700111926376	0.157724093286753	0.455669198630123	0.648770822440153	   
df.mm.trans1:exp3	0.124535874937953	0.198673932622351	0.626835505263172	0.530973806094429	   
df.mm.trans2:exp3	-0.0167887581443810	0.157724093286753	-0.106443839964627	0.915261060857838	   
df.mm.trans1:exp4	0.0773909609397078	0.198673932622351	0.38953757001839	0.69699837431743	   
df.mm.trans2:exp4	-0.055933965558519	0.157724093286753	-0.354631714108683	0.722973558507037	   
df.mm.trans1:exp5	0.0176181072526575	0.198673932622351	0.0886785046236884	0.929363073146774	   
df.mm.trans2:exp5	-0.168034234544526	0.157724093286753	-1.06536820750035	0.287080912765871	   
df.mm.trans1:exp6	-0.094488193689425	0.198673932622351	-0.475594319004259	0.634513515178976	   
df.mm.trans2:exp6	-0.0359858251064463	0.157724093286753	-0.228156804433306	0.81959174099984	   
df.mm.trans1:exp7	-0.0779142404129767	0.198673932622351	-0.392171430768826	0.695052303630048	   
df.mm.trans2:exp7	0.0604834536773575	0.157724093286753	0.383476312445141	0.701484411380303	   
df.mm.trans1:exp8	-0.165398579159085	0.198673932622351	-0.832512735696852	0.40540680639272	   
df.mm.trans2:exp8	-0.109538653287707	0.157724093286753	-0.69449537483508	0.487604695272246	   
df.mm.trans1:probe2	0.170280382884603	0.138402330162497	1.23032887296535	0.218992041453573	   
df.mm.trans1:probe3	0.0732535029140885	0.138402330162497	0.529279404675355	0.596781380566206	   
df.mm.trans1:probe4	0.140029419576843	0.138402330162497	1.01175622847126	0.312008249467861	   
df.mm.trans1:probe5	0.108578012690088	0.138402330162497	0.784510004727578	0.433009382029172	   
df.mm.trans1:probe6	0.136107688518608	0.138402330162497	0.98342049847575	0.325744227189917	   
df.mm.trans1:probe7	-0.0629601784912786	0.138402330162497	-0.454906925464026	0.649318876807512	   
df.mm.trans1:probe8	-0.0191983813606774	0.138402330162497	-0.138714292874525	0.889716279802279	   
df.mm.trans1:probe9	0.0111395507822534	0.138402330162497	0.0804867285772904	0.935873422152341	   
df.mm.trans1:probe10	-0.0828226676762603	0.138402330162497	-0.598419604489454	0.54975580237104	   
df.mm.trans1:probe11	0.0390693328225334	0.138402330162497	0.282288114489564	0.777807005136156	   
df.mm.trans1:probe12	-0.0844247508973923	0.138402330162497	-0.609995155415879	0.542065268726541	   
df.mm.trans1:probe13	-0.0657961279819743	0.138402330162497	-0.475397545003206	0.634653664744512	   
df.mm.trans1:probe14	-0.117244877569363	0.138402330162497	-0.847130806480693	0.397215092047525	   
df.mm.trans2:probe2	-0.138529225087746	0.138402330162497	-1.00091685541060	0.317216869510127	   
df.mm.trans2:probe3	-0.173480997856381	0.138402330162497	-1.25345431433631	0.210463737883148	   
df.mm.trans2:probe4	0.0545635046505893	0.138402330162497	0.394238338231204	0.69352654365545	   
df.mm.trans2:probe5	-0.0180890774638688	0.138402330162497	-0.130699226253131	0.896051229634811	   
df.mm.trans2:probe6	-0.117090296787781	0.138402330162497	-0.846013912123491	0.397837428001209	   
df.mm.trans3:probe2	0.0522399346182824	0.138402330162497	0.377449820078519	0.705955080742537	   
df.mm.trans3:probe3	-0.125032138362152	0.138402330162497	-0.903396194380202	0.366630023176631	   
df.mm.trans3:probe4	-0.130017431320228	0.138402330162497	-0.939416490803125	0.347844731113632	   
df.mm.trans3:probe5	0.156481648824642	0.138402330162497	1.13062871586713	0.25860309969982	   
df.mm.trans3:probe6	0.103091555290926	0.138402330162497	0.744868638915883	0.456604025634673	   
df.mm.trans3:probe7	-0.106776012364967	0.138402330162497	-0.771489990375175	0.440679910167907	   
df.mm.trans3:probe8	0.250688550663476	0.138402330162497	1.81130296266793	0.0705274171142066	.  
df.mm.trans3:probe9	-0.0434443004370645	0.138402330162497	-0.313898619958616	0.753692639486996	   
df.mm.trans3:probe10	-0.117401517541303	0.138402330162497	-0.848262579130447	0.396585066483105	   
df.mm.trans3:probe11	-0.247350588998160	0.138402330162497	-1.78718514860081	0.0743451367156876	.